class_docstr: Cornell subset of
  `WebKB <http://www.cs.cmu.edu/afs/cs.cmu.edu/project/theo-11/www/wwkb/>`__,
  later modified by `Geom-GCN: Geometric Graph Convolutional Networks
  <https://arxiv.org/abs/2002.05287>`__
  
  Nodes represent web pages. Edges represent hyperlinks between them. Node
  features are the bag-of-words representation of web pages. The web pages
  are manually classified into the five categories, student, project, course,
  staff, and faculty.
  
  Statistics:
  
  - Nodes: 183
  - Edges: 298
  - Number of Classes: 5
  - 10 train/val/test splits
  
      - Train: 87
      - Val: 59
      - Test: 37
  
  Parameters
  ----------
  raw_dir : str, optional
      Raw file directory to store the processed data. Default: ~/.dgl/
  force_reload : bool, optional
      Whether to re-download the data source. Default: False
  verbose : bool, optional
      Whether to print progress information. Default: True
  transform : callable, optional
      A transform that takes in a :class:`~dgl.DGLGraph` object and returns
      a transformed version. The :class:`~dgl.DGLGraph` object will be
      transformed before every access. Default: None
  
  Attributes
  ----------
  num_classes : int
      Number of node classes
  
  Notes
  -----
  The graph does not come with edges for both directions.
  
  Examples
  --------
  
  >>> from dgl.data import CornellDataset
  >>> dataset = CornellDataset()
  >>> g = dataset[0]
  >>> num_classes = dataset.num_classes
  
  >>> # get node features
  >>> feat = g.ndata["feat"]
  
  >>> # get data split
  >>> train_mask = g.ndata["train_mask"]
  >>> val_mask = g.ndata["val_mask"]
  >>> test_mask = g.ndata["test_mask"]
  
  >>> # get labels
  >>> label = g.ndata['label']
code: def __init__(
      self,
      raw_dir=None,
      force_reload=False,
      verbose=True,
      transform=None,
  ):
      super(CornellDataset, self).__init__(
          name="cornell",
          raw_dir=raw_dir,
          force_reload=force_reload,
          verbose=verbose,
          transform=transform,
      )
  
imports: import os
  import numpy
  from ..convert import graph
  from .dgl_dataset import DGLBuiltinDataset
  from .utils import _get_dgl_url
label_desc: Use image node_id 1 to create a new CornellDataset object from inherited base classes: GeomGCNDataset with example: obj = CornellDataset(raw_dir, force_reload, verbose, transform)